Abstract
The assessment of research and development (R&D) innovation is inherently a multiple criteria decision making (MCDM) problem and has become a fundamental concern for R&D managers in the last decades. Research in identifying the relative importance of criteria used to select a favorable project has relied on subjective lists of criteria being presented to R&D managers. The conventional methods for evaluating corresponding R&D merits are inadequate for dealing with suchlike imprecise, heterogeneity or uncertainty of linguistic assessment. Whereas most attributes and their weights are linguistic variables and not easily quantifiable, 2-tuple fuzzy linguistic representation and multigranular linguistic computing manner are applied to transform the heterogeneous information assessed by multiple experts into a common domain and style. It is advantageous to retain consistency of evaluations. The proposed linguistic computing approach integrates the heterogeneity and determines the overall quality level and the performance with respect to specific quality attributes of an R&D innovation.
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References
Eilat, H., Golany, B., Shtub, A.: R&D Project Evaluation: An Integrated DEA and Balanced Scorecard Approach. Omega-Int. J. Manage. S. 36(5), 895–912 (2008)
Huang, C.C., Chu, P.Y., Chiang, Y.H.: A Fuzzy AHP Application in Government- Sponsored R&D Project Selection. Omega-Int. J. Manage. S. 36(6), 1038–1052 (2008)
Kim, B., Oh, H.: An Effective R&D Performance Measurement System: Survey of Korean R&D Researchers. Omega-Int. J. Manage. S. 30(1), 19–31 (2002)
Mohanty, R.P., Agarwal, R., Choudhury, A.K., Tiwari, M.K.: A fuzzy ANP-based approach to R&D project selection: a case study. Int. J. Prod. Res. 43(24), 5199–5216 (2005)
Hélène Sicotte, H., Langley, A.: Integration Mechanisms and R&D Project Performance. J. Eng. Technol. Manage. 17(1), 1–37 (2000)
Huang, Y.A., Chung, H.J., Lin, C.: R&D Sourcing Strategies: Determinants and Consequences. Technovation 29(3), 155–169 (2009)
Pillai, A.S., Joshi, A., Rao, K.S.: Performance Measurement of R&D Projects in a Multi-Project, Concurrent Engineering Environment. Int. J. Proj. Manag. 20(2), 165–177 (2002)
Klapka, J., Piňos, P.: Decision Support System for Multicriterial R&D and Information Systems Projects Selection. Eur. J. Oper. Res. 140(2), 434–446 (2002)
Chen, S.J., Hwang, C.L.: Fuzzy Multiple Attribute Decision Making–Methods and Applications. Springer, New York (1992)
Hwang, C.L., Yoon, K.: Multiple Attributes Decision Making Methods and Applications. Springer, New York (1981)
Wang, W.P.: Toward Developing Agility Evaluation of Mass Customization Systems Using 2-Tuple Linguistic Computing. Expert Syst. Appl. 36(2), 3439–3447 (2009)
Wi, H., Jung, M.: Modeling and Analysis of Project Performance Factors in an Extended Project-Oriented Virtual Organization (EProVO). Expert Syst. Appl. 37(2), 1143–1151 (2010)
Meade, L.M., Presley, A.: R&D Project Selection Using the Analytic Network Process. IEEE T. Eng. Manage. 49(1), 59–66 (2002)
Baker, N., Freeland, J.: Recent Advances in R&D Benefit Measurement and Project Selection Methods. Manage. Sci. 21(10), 1164–1175 (1975)
Hwang, H.S., Yu, J.C.: R&D Project Evaluation Model Based on Fuzzy Set Priority. Comput. Ind. Eng. 35(3-4), 567–570 (1998)
Herrera-Viedma, E., Herrera, F., Martinez, L., Herrera, J.C., Lopez, A.G.: Incorporating Filtering Techniques in a Fuzzy Linguistic Multi-Agent Model for Information Gathering on the Web. Fuzzy Set Syst. 148(1), 61–83 (2004)
Zadeh, L.A.: The Concept of a Linguistic Variable and its Application to Approximate Reasoning. Inform. Sciences 8(3, 4), 199–249(pt. I), 301–357(pt. II) (1975)
Herrera, F., Martinez, L.: An Approach for Combining Linguistic and Numerical Information Based on 2-Tuple Fuzzy Representation Model in Decision-Making. Int. J. Uncertain. Fuzz. 8(5), 539–562 (2000)
Herrera, F., Martinez, L.: A Model Based on Linguistic 2-Tuples for Dealing with Multigranular Hierarchical Linguistic Contexts in Multi-Expert Decision-Making. IEEE T. Syst. Man Cy. B 31(2), 227–234 (2001)
Tai, W.S., Chen, C.T.: A new evaluation model for intellectual capital based on computing with linguistic variable. Expert Syst. Appl. 36(2), 3483–3488 (2009)
Herrera, F., Martinez, L., Sanchez, J.: Managing Non-Homogeneous Information in Group Decision Making. Eur. J. Oper. Res. 166, 115–132 (2005)
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Wang, WP., Tang, MC. (2015). A Multi-criteria Assessment for R&D Innovation with Fuzzy Computing with Words. In: Le Thi, H., Pham Dinh, T., Nguyen, N. (eds) Modelling, Computation and Optimization in Information Systems and Management Sciences. Advances in Intelligent Systems and Computing, vol 360. Springer, Cham. https://doi.org/10.1007/978-3-319-18167-7_1
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DOI: https://doi.org/10.1007/978-3-319-18167-7_1
Publisher Name: Springer, Cham
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